Parameter Optimization of PID Controllers by Reinforcement Learning
文献类型：会议论文
| 作者 | Shang, X.Y.; Ji, T.Y.; Li, M.S.; Wu, P.Z.; Wu, Q.H. |
| 出版日期 | 2013 |
| 会议名称 | 2013 5th Computer Science and Electronic Engineering Conference, CEEC 2013 |
| 会议地点 | Colchester, United kingdom |
| 英文摘要 | This paper focuses on implementing a reinforcement learning algorithm for solving parameter optimization problems of Proportional Integral Derivative (PID) controllers. Function Optimization by Reinforcement Learning (FORL) remarkably outperforms a number of population-based intelligent algorithms when executed on benchmark functions in high-dimension circumstances. Therefore, this paper aims at examining the performance of FORL when optimizing parameters of PID controllers in a low-dimension space. According to the experiment studies in this paper, FORL is able to optimize the PID parameters with advantage over GA and PSO in terms of convergence speed. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4921]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Shang, X.Y.,Ji, T.Y.,Li, M.S.,et al. Parameter Optimization of PID Controllers by Reinforcement Learning[C]. 见:2013 5th Computer Science and Electronic Engineering Conference, CEEC 2013. Colchester, United kingdom. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。